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  • 1
    Publication Date: 2016-06-21
    Description: Identifying coding genes is an essential step in genome annotation. Here, we utilize existing whole genome alignments to detect conserved coding exons and then map gene annotations from one genome to many aligned genomes. We show that genome alignments contain thousands of spurious frameshifts and splice site mutations in exons that are truly conserved. To overcome these limitations, we have developed CESAR (Coding Exon-Structure Aware Realigner) that realigns coding exons, while considering reading frame and splice sites of each exon. CESAR effectively avoids spurious frameshifts in conserved genes and detects 91% of shifted splice sites. This results in the identification of thousands of additional conserved exons and 99% of the exons that lack inactivating mutations match real exons. Finally, to demonstrate the potential of using CESAR for comparative gene annotation, we applied it to 188 788 exons of 19 865 human genes to annotate human genes in 99 other vertebrates. These comparative gene annotations are available as a resource ( http://bds.mpi-cbg.de/hillerlab/CESAR/ ). CESAR ( https://github.com/hillerlab/CESAR/ ) can readily be applied to other alignments to accurately annotate coding genes in many other vertebrate and invertebrate genomes.
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 2
    Publication Date: 2015-12-16
    Description: The enrichment of targeted regions within complex next generation sequencing libraries commonly uses biotinylated baits to capture the desired sequences. This method results in high read coverage over the targets and their flanking regions. Oxford Nanopore Technologies recently released an USB3.0-interfaced sequencer, the MinION. To date no particular method for enriching MinION libraries has been standardized. Here, using biotinylated PCR-generated baits in a novel approach, we describe a simple and efficient way for multiplexed enrichment of MinION libraries, overcoming technical limitations related with the chemistry of the sequencing-adapters and the length of the DNA fragments. Using Phage Lambda and Escherichia coli as models we selectively enrich for specific targets, significantly increasing the corresponding read-coverage, eliminating unwanted regions. We show that by capturing genomic fragments, which contain the target sequences, we recover reads extending targeted regions and thus can be used for the determination of potentially unknown flanking sequences. By pooling enriched libraries derived from two distinct E. coli strains and analyzing them in parallel, we demonstrate the efficiency of this method in multiplexed format. Crucially we evaluated the optimal bait size for large fragment libraries and we describe for the first time a standardized method for target enrichment in MinION platform.
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 3
    Publication Date: 2015-05-20
    Description: Single-cell mRNA sequencing (RNA-seq) methods have undergone rapid development in recent years, and transcriptome analysis of relevant cell populations at single-cell resolution has become a key research area of biomedical sciences. We here present s ingle- c ell mRNA 3 -prime end seq uencing (SC3-seq), a practical methodology based on PCR amplification followed by 3-prime-end enrichment for highly quantitative, parallel and cost-effective measurement of gene expression in single cells. The SC3-seq allows excellent quantitative measurement of mRNAs ranging from the 10,000-cell to 1-cell level, and accordingly, allows an accurate estimate of the transcript levels by a regression of the read counts of spike-in RNAs with defined copy numbers. The SC3-seq has clear advantages over other typical single-cell RNA-seq methodologies for the quantitative measurement of transcript levels and at a sequence depth required for the saturation of transcript detection. The SC3-seq distinguishes four distinct cell types in the peri-implantation mouse blastocysts. Furthermore, the SC3-seq reveals the heterogeneity in human-induced pluripotent stem cells (hiPSCs) cultured under on-feeder as well as feeder-free conditions, demonstrating a more homogeneous property of the feeder-free hiPSCs. We propose that SC3-seq might be used as a powerful strategy for single-cell transcriptome analysis in a broad range of investigations in biomedical sciences.
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 4
    Publication Date: 2015-06-24
    Description: Whole exome sequencing (WES) is increasingly used in research and diagnostics. WES users expect coverage of the entire coding region of known genes as well as sufficient read depth for the covered regions. It is, however, unknown which recent WES platform is most suitable to meet these expectations. We present insights into the performance of the most recent standard exome enrichment platforms from Agilent, NimbleGen and Illumina applied to six different DNA samples by two sequencing vendors per platform. Our results suggest that both Agilent and NimbleGen overall perform better than Illumina and that the high enrichment performance of Agilent is stable among samples and between vendors, whereas NimbleGen is only able to achieve vendor- and sample-specific best exome coverage. Moreover, the recent Agilent platform overall captures more coding exons with sufficient read depth than NimbleGen and Illumina. Due to considerable gaps in effective exome coverage, however, the three platforms cannot capture all known coding exons alone or in combination, requiring improvement. Our data emphasize the importance of evaluation of updated platform versions and suggest that enrichment-free whole genome sequencing can overcome the limitations of WES in sufficiently covering coding exons, especially GC-rich regions, and in characterizing structural variants.
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 5
    Publication Date: 2016-03-01
    Description: Adequate read filtering is critical when processing high-throughput data in marker-gene-based studies. Sequencing errors can cause the mis-clustering of otherwise similar reads, artificially increasing the number of retrieved Operational Taxonomic Units (OTUs) and therefore leading to the overestimation of microbial diversity. Sequencing errors will also result in OTUs that are not accurate reconstructions of the original biological sequences. Herein we present the Poisson binomial filtering algorithm (PBF), which minimizes both problems by calculating the error-probability distribution of a sequence from its quality scores. In order to validate our method, we quality-filtered 37 publicly available datasets obtained by sequencing mock and environmental microbial communities with the Roche 454, Illumina MiSeq and IonTorrent PGM platforms, and compared our results to those obtained with previous approaches such as the ones included in mothur, QIIME and USEARCH. Our algorithm retained substantially more reads than its predecessors, while resulting in fewer and more accurate OTUs. This improved sensitiveness produced more faithful representations, both quantitatively and qualitatively, of the true microbial diversity present in the studied samples. Furthermore, the method introduced in this work is computationally inexpensive and can be readily applied in conjunction with any existent analysis pipeline.
    Keywords: Massively Parallel (Deep) Sequencing
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    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 6
    Publication Date: 2015-12-02
    Description: Highly abundant microRNAs (miRNAs) in small RNA sequencing libraries make it difficult to obtain efficient measurements of more lowly expressed species. We present a new method that allows for the selective blocking of specific, abundant miRNAs during preparation of sequencing libraries. This technique is specific with little off-target effects and has no impact on the reproducibility of the measurement of non-targeted species. In human plasma samples, we demonstrate that blocking of highly abundant hsa-miR-16–5p leads to improved detection of lowly expressed miRNAs and more precise measurement of differential expression overall. Furthermore, we establish the ability to target a second abundant miRNA and to multiplex the blocking of two miRNAs simultaneously. For small RNA sequencing, this technique could fill a similar role as do ribosomal or globin removal technologies in messenger RNA sequencing.
    Keywords: Massively Parallel (Deep) Sequencing
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    Topics: Biology
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  • 7
    Publication Date: 2015-04-02
    Description: Next-generation sequencing has been widely used for the genome-wide profiling of histone modifications, transcription factor binding and gene expression through chromatin immunoprecipitated DNA sequencing (ChIP-seq) and cDNA sequencing (RNA-seq). Here, we describe a versatile library construction method that can be applied to both ChIP-seq and RNA-seq on the widely used Illumina platforms. Standard methods for ChIP-seq library construction require nanograms of starting DNA, substantially limiting its application to rare cell types or limited clinical samples. By minimizing the DNA purification steps that cause major sample loss, our method achieved a high sensitivity in ChIP-seq library preparation. Using this method, we achieved the following: (i) generated high-quality epigenomic and transcription factor-binding maps using ChIP-seq for murine adipocytes; (ii) successfully prepared a ChIP-seq library from as little as 25 pg of starting DNA; (iii) achieved paired-end sequencing of the ChIP-seq libraries; (iv) systematically profiled gene expression dynamics during murine adipogenesis using RNA-seq and (v) preserved the strand specificity of the transcripts in RNA-seq. Given its sensitivity and versatility in both double-stranded and single-stranded DNA library construction, this method has wide applications in genomic, epigenomic, transcriptomic and interactomic studies.
    Keywords: Massively Parallel (Deep) Sequencing
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    Topics: Biology
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  • 8
    Publication Date: 2015-01-10
    Description: Deep sequencing of strand-specific cDNA libraries is now a ubiquitous tool for identifying and quantifying RNAs in diverse sample types. The accuracy of conclusions drawn from these analyses depends on precise and quantitative conversion of the RNA sample into a DNA library suitable for sequencing. Here, we describe an optimized method of preparing strand-specific RNA deep sequencing libraries from small RNAs and variably sized RNA fragments obtained from ribonucleoprotein particle footprinting experiments or fragmentation of long RNAs. Our approach works across a wide range of input amounts (400 pg to 200 ng), is easy to follow and produces a library in 2–3 days at relatively low reagent cost, all while giving the user complete control over every step. Because all enzymatic reactions were optimized and driven to apparent completion, sequence diversity and species abundance in the input sample are well preserved.
    Keywords: Massively Parallel (Deep) Sequencing
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  • 9
    Publication Date: 2016-11-01
    Description: Genome assemblies that are accurate, complete and contiguous are essential for identifying important structural and functional elements of genomes and for identifying genetic variation. Nevertheless, most recent genome assemblies remain incomplete and fragmented. While long molecule sequencing promises to deliver more complete genome assemblies with fewer gaps, concerns about error rates, low yields, stringent DNA requirements and uncertainty about best practices may discourage many investigators from adopting this technology. Here, in conjunction with the platinum standard Drosophila melanogaster reference genome, we analyze recently published long molecule sequencing data to identify what governs completeness and contiguity of genome assemblies. We also present a hybrid meta-assembly approach that achieves remarkable assembly contiguity for both Drosophila and human assemblies with only modest long molecule sequencing coverage. Our results motivate a set of preliminary best practices for obtaining accurate and contiguous assemblies, a ‘missing manual’ that guides key decisions in building high quality de novo genome assemblies, from DNA isolation to polishing the assembly.
    Keywords: Massively Parallel (Deep) Sequencing
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  • 10
    Publication Date: 2015-11-17
    Description: Various biases affect high-throughput sequencing read counts. Contrary to the general assumption, we show that bias does not always cancel out when fold changes are computed and that bias affects more than 20% of genes that are called differentially regulated in RNA-seq experiments with drastic effects on subsequent biological interpretation. Here, we propose a novel approach to estimate fold changes. Our method is based on a probabilistic model that directly incorporates count ratios instead of read counts. It provides a theoretical foundation for pseudo-counts and can be used to estimate fold change credible intervals as well as normalization factors that outperform currently used normalization methods. We show that fold change estimates are significantly improved by our method by comparing RNA-seq derived fold changes to qPCR data from the MAQC/SEQC project as a reference and analyzing random barcoded sequencing data. Our software implementation is freely available from the project website http://www.bio.ifi.lmu.de/software/lfc .
    Keywords: Massively Parallel (Deep) Sequencing
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  • 11
    Publication Date: 2015-11-17
    Description: The human reference assembly remains incomplete due to the underrepresentation of repeat-rich sequences that are found within centromeric regions and acrocentric short arms. Although these sequences are marginally represented in the assembly, they are often fully represented in whole-genome short-read datasets and contribute to inappropriate alignments and high read-depth signals that localize to a small number of assembled homologous regions. As a consequence, these regions often provide artifactual peak calls that confound hypothesis testing and large-scale genomic studies. To address this problem, we have constructed mapping targets that represent roughly 8% of the human genome generally omitted from the human reference assembly. By integrating these data into standard mapping and peak-calling pipelines we demonstrate a 10-fold reduction in signals in regions common to the blacklisted region and identify a comprehensive set of regions that exhibit mapping sensitivity with the presence of the repeat-rich targets.
    Keywords: Massively Parallel (Deep) Sequencing
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    Topics: Biology
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  • 12
    Publication Date: 2015-08-18
    Description: There is an increasing interest in complementing RNA-seq experiments with small-RNA (sRNA) expression data to obtain a comprehensive view of a transcriptome. Currently, two main experimental challenges concerning sRNA-seq exist: how to check the size distribution of isolated sRNAs, given the sensitive size-selection steps in the protocol; and how to normalize data between samples, given the low complexity of sRNA types. We here present two separate sets of synthetic RNA spike-ins for monitoring size-selection and for performing data normalization in sRNA-seq. The size-range quality control (SRQC) spike-in set, consisting of 11 oligoribonucleotides (10–70 nucleotides), was tested by intentionally altering the size-selection protocol and verified via several comparative experiments. We demonstrate that the SRQC set is useful to reproducibly track down biases in the size-selection in sRNA-seq. The external reference for data-normalization (ERDN) spike-in set, consisting of 19 oligoribonucleotides, was developed for sample-to-sample normalization in differential-expression analysis of sRNA-seq data. Testing and applying the ERDN set showed that it can reproducibly detect differential expression over a dynamic range of 2 18 . Hence, biological variation in sRNA composition and content between samples is preserved while technical variation is effectively minimized. Together, both spike-in sets can significantly improve the technical reproducibility of sRNA-seq.
    Keywords: Massively Parallel (Deep) Sequencing
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    Topics: Biology
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